TY  - JOUR
A1  - Neyer, Franz J.
A1  - Felber, Juliane
A1  - Gebhardt, Claudia
T1  - Development and validation of a brief measure of technology commitment
JF  - Diagnostica
N2  - The authors propose a model of technology commitment that describes individual differences in the willingness of technology use in terms of three facets: technology acceptance, technology competence, technology control. It is assumed that technology commitment predicts adaptive technology use especially in old age. Data from three studies (N = 825 participants) support the conceptual distinction of the constructs and confirm the psychometric properties of the newly constructed scale. Construct validity was established via correlations with theoretically related constructs (technology use, personality, successful aging, health) as well as concurrently vis-a-vis other measures of technology acceptance.
KW  - technology commitment
KW  - technology acceptance
KW  - technology competence
KW  - technology control
KW  - technology use
Y1  - 2012
U6  - https://doi.org/10.1026/0012-1924/a000067
SN  - 0012-1924
VL  - 58
IS  - 2
SP  - 87
EP  - 99
PB  - Hogrefe
CY  - Göttingen
ER  - 
TY  - JOUR
A1  - Vladova, Gergana
A1  - Ullrich, André
A1  - Bender, Benedict
A1  - Gronau, Norbert
T1  - Students’ acceptance of technology-mediated teaching – How it was influenced during the COVID-19 Pandemic in 2020
BT  - A study from Germany
JF  - Frontiers in psychology / Frontiers Research Foundation
N2  - In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
KW  - COVID-19
KW  - digital learning
KW  - discipline differences
KW  - e-learning
KW  - TAM
KW  - technology acceptance
KW  - technology-mediated teaching
KW  - university teaching
Y1  - 2020
U6  - https://doi.org/10.3389/fpsyg.2021.636086
SN  - 1664-1078
VL  - 12
PB  - Frontiers Research Foundation
CY  - Lausanne
ER  -